1. Field of the Invention
The present invention generally relates to image processing apparatuses and methods, program recording media, and programs. More particularly, the invention relates to an image processing apparatus and method, a program recording medium, and a program that allow the quality of an image to be accurately enhanced by distinguishing artificial image components and natural image components included in an image from each other and by performing optimal processing on each of the artificial image components and natural image components.
2. Description of the Related Art
The assignee of this application previously proposed classification adaptation processing in, for example, Japanese Unexamined Patent Application Publication No. 9- 167240. In the classification adaptation processing, from an input first image, a second image is determined. More specifically, according to the pixel values of a plurality of pixels in a predetermined area of the input first image, subject pixels of the second image are allocated into classes, and then, a linear expression of prediction coefficients which have been determined for the individual classes by learning processing, and the pixel values of the plurality of pixels in the predetermined area of the input first image are calculated, so that the second image can be determined from the input first image.
For example, if the first image is an image containing noise and the second image is an image with suppressed noise, the classification adaptation processing serves as noise suppression processing. If the first image is a standard definition (SD) image and the second image is a high definition (HD) image with a level of resolution higher than that of the SD image, the classification adaptation processing serves as resolution conversion processing for converting a low-resolution image into a high-resolution image.
In known learning processing, to enable prediction of general moving pictures typified by broadcasting moving pictures, instead of artificial images, which are discussed in detail below, natural images obtained by directly imaging subjects in nature are used as supervisor images and learner images. Accordingly, if the first image is a natural image, the second image, which is a high-definition, fine image, can be predicted by performing classification adaptation processing using prediction coefficients obtained by learning processing.